1. Robin L. Donaldson April 29, 2011 Dissertation Defense Florida State University College of Communication and Information 1Copyright Robin Lee Donaldson. All rights reserved.

2. Study of technology acceptance using IS theories has received extensive attention from research in information systems, library information studies, and from education researchers, however: Limited research using IS models Mobile learning may have unique characteristic IS models may not fully address mobile learning Impact of mobile devices on higher education and use for access to library and information resources is unclear 2Copyright Robin Lee Donaldson. All rights reserved.

3. Use technology acceptance theory as a theoretical framework to examine the determinants associated with community college students acceptance and use of mobile learning. 3Copyright Robin Lee Donaldson. All rights reserved.

4. Performance Expectancy the degree to which an individual believes that using the system will help him or her to attain gains in job performance Effort Expectancy the degree of ease associated with the use of the system Social Influence the degree to which an individual perceives that important others believe he or she should use the new system Facilitating Conditions the degree to which an individual believes that an organizational and technical infrastructure exists to support use of the system 4Copyright Robin Lee Donaldson. All rights reserved.

5. Self-management of learning is the extent to which an individual feels he or she is self- disciplined and can engage in autonomous learning 5Copyright Robin Lee Donaldson. All rights reserved.

6. Perceived playfulness -a state of mind that includes three dimensions: the extent to which the individual: perceives that his or her attention is focused, curious during and finds the interaction intrinsically enjoyable or interesting. 6Copyright Robin Lee Donaldson. All rights reserved.

7. Voluntariness of Use the degree to which use of the innovation is perceived as being voluntary, or of free will 7Copyright Robin Lee Donaldson. All rights reserved.

8. Mixed Method Procedure Archival survey analysis Interviews 8Copyright Robin Lee Donaldson. All rights reserved.

9. Archival survey data UTAUT -Venkatesh, Morris, Davis, and Davis (2003) Wang, Wu, and Wang (2008) Demographic and opinion-related questions gender/age access to a home computer Internet experience; frequency of use of mobile devices; types of information, and library and learning resources currently used and interested in accessing 9Copyright Robin Lee Donaldson. All rights reserved.

10. Likert scales (1–7) Anchors 1Strongly agree 2Agree 3Moderately agree 4Slightly agree 5Neutral 6Disagree 7Strongly disagree 10Copyright Robin Lee Donaldson. All rights reserved.

11. Community College in North Florida Convenience Sample Students enrolled in credit courses 330 participants Average Age: 27 Gender: Females: 61.8% Males: 38.2% 11Copyright Robin Lee Donaldson. All rights reserved.

12. a-priori power analysis No. of participants required to detect a medium effect size (d =.50) with power =.80 for a two-tailed independent samples t-test at a =.05. Suggested that 128 needed to achieve a power of.80 given these parameters Statistical software G*Power 3.0.8 12Copyright Robin Lee Donaldson. All rights reserved.

13. Is there a statistically significant difference between males and females on the behavioral intention to use mobile learning? H 0 : There will be no statistically significant difference between the males and females on the behavioral intention to use mobile learning. Analysis: independent samples t-test 13Copyright Robin Lee Donaldson. All rights reserved.

14. t (289) = -2.03, p <.05 14Copyright Robin Lee Donaldson. All rights reserved.

15. Are there statistically significant relationships among the participants age, behavioral intention to use mobile learning and the actual use of mobile learning? H 0 : There will not be a statistically significant relationship between the participants age and their behavioral intention to use mobile learning. Analysis: Simple linear regression 15Copyright Robin Lee Donaldson. All rights reserved.

16. F (1, 266) = 0.03, = 0.01, p >.05, R 2 =.00 16Copyright Robin Lee Donaldson. All rights reserved.

17. 17Copyright Robin Lee Donaldson. All rights reserved.

18. Are the following independent variables significant predictors of the behavioral intention to use mobile learning: Analysis: multiple regression 1.performance expectancy 2.effort expectancy 3.social influence 4.facilitating conditions 5.perceived playfulness 6.self-management of learning 7.voluntariness of use 18Copyright Robin Lee Donaldson. All rights reserved.

19. 19Copyright Robin Lee Donaldson. All rights reserved.

20. Demographic and opinion-related questions Personal activities Frequency of Internet access Internet experience Types of information, and library and learning resources currently used and interested in accessing 20Copyright Robin Lee Donaldson. All rights reserved.

21. n=314 21Copyright Robin Lee Donaldson. All rights reserved.

22. 22Copyright Robin Lee Donaldson. All rights reserved.

23. 23Copyright Robin Lee Donaldson. All rights reserved.

24. 24Copyright Robin Lee Donaldson. All rights reserved.

25. 25Copyright Robin Lee Donaldson. All rights reserved.

26. Gather additional data not revealed in survey Increase understanding of determinants, barriers, and perceptions on use Determinates of acceptance expected but not pre-designed in interview 26Copyright Robin Lee Donaldson. All rights reserved.

27. Research Question 4 - What factors influence community college students use of mobile devices for learning? 27Copyright Robin Lee Donaldson. All rights reserved.

28. Research Setting – same Sample Population - same Participants - 20 Convenience sampling Selecting participants Courses targeted – diverse disciplines, level, and utilize library or online resources 28Copyright Robin Lee Donaldson. All rights reserved.

29. Semi structured Research question guide discussion Protocol One interviewer Script Face-to-face, online, or phone Coded using inductive analysis Themes (16) derived from interview data 29Copyright Robin Lee Donaldson. All rights reserved.

30. Ownership, acceptance, device attributes, cost, and mobile access to academic services Knowledge of Library Resources No knowledge of availability & benefits (35%) I dont really know if I can access all that information 30Copyright Robin Lee Donaldson. All rights reserved.

31. 90% felt mobile learning useful for supporting learning Manage time Productive Organize thoughts & tasks Prepare for class 85% use calendar function 40% - Anywhere/anytime access (mobility) 31Copyright Robin Lee Donaldson. All rights reserved.

32. 70% Facebook & 60% texting classmates …Makes it easier to kind of actually form a community in a sense. Form a communityand you actually get to know people and study together and things like that. Faculty respond quicker than email..usually within the hour Too personal, not professional, keep school separate, not give faculty personal phone number (30%) 32Copyright Robin Lee Donaldson. All rights reserved.

33. Overall, not perceived as supporting or recommending use in or outside of the classroom..older instructors arent real comfortable accepting new tecnology… …never actually spoke to a professor about it because normally they just dont want to see your phone. Turn off in class/out of hands – no note taking Instances of support were provided by some May readily accept learning if faculty or their peers do so and feel it is beneficial 33Copyright Robin Lee Donaldson. All rights reserved.

34. No direct question 35% Identified playfulness component …more likely to do it because it wouldnt seem much of a chore… fun Lose track of time or explore further 34Copyright Robin Lee Donaldson. All rights reserved.

35. Suggests no significant difference between males and females and intended use of mobile learning. Findings were unexpected Prior research - moderating effect of gender on predictor variables This research – examined differences between males and females on BI Need additional research 35Copyright Robin Lee Donaldson. All rights reserved.

36. Suggests age does not have a relationship with intention to use mobile learning Findings were unexpected Prior - Wang, Wu, Wang (2008) research - moderating effect of gender on predictor variables. Computer literature suggest a there is an age relationship This research – examined differences between males and females on BI May be due to the age range of the participants 27.13 years average Nine out of ten 18-29 year old more likely to use mobile data applications 65% access the Internet from their cell phones (Smith, 2010) Need additional research 36Copyright Robin Lee Donaldson. All rights reserved.

37. Omnibus model accounts for 75 % percent of the variance in BI to use UTAUT study (70%) Wang et al., (2008) (58%) Regression coefficients for all respondents *p < 0.05 **p < 0.01 37Copyright Robin Lee Donaldson. All rights reserved.

38. Clear interest in mobile access to learning and library information content Experience with browsing/searching on mobile devices higher levels of BI to use, perceived ease of use, and perceived usefulness of mobile learning (Akour, 2009) Potential to reduce digital divide (Hahn,2008) Increased usage for personal purposes may lead to increased demand for mobile academic purposes 38Copyright Robin Lee Donaldson. All rights reserved.

39. Students are interested in mobile access to library resources and services Point toward the need to familiarize students with: benefits of mobile access to library resources mobile library resources available completing various learning tasks, recommendations for applications 39Copyright Robin Lee Donaldson. All rights reserved.

40. Point toward the need to: provide support for mobile access to services assist students in gaining necessary skills and knowledge to successfully use mobile learning promote the performance benefits of usage 40Copyright Robin Lee Donaldson. All rights reserved.

41. Point toward the need to familiarize students with: ways to support both classroom and remote learning available instructional mobile resources performance benefits and playfulness aspect and providing content and information on resources formatted for mobile devices 41Copyright Robin Lee Donaldson. All rights reserved.

42. Convenience sample Cross sectional Single community college -not generalizabile Statistical significance within the design does not imply cause- and-effect relationships Predictors identified may not be found to be predictors in other mobile learning research. Those that were not found to be predictors may be found to be predictors in other mobile learning research 42Copyright Robin Lee Donaldson. All rights reserved.

43. Examine self-management alone to understand its importance as a predictor in mobile learning. Examine the significance of the predictors for educators. Examine effort expectancy using individuals with varying levels of experience with mobile devices and a wider age range of users. Similar research on mobility as a significant predictor for access to digital resources and support from academic libraries 43Copyright Robin Lee Donaldson. All rights reserved.

44. 44Copyright Robin Lee Donaldson. All rights reserved.

45. 45 Schaefer, Andreas (2008). iX-ray. Retrieved from: http://flickrcc.bluemountains.net http://flickrcc.bluemountains.net Also available in multiple sizes at Flickr Website: http://www.flickr.com/photos/36266791@N00/2986303105 http://www.flickr.com/photos/36266791@N00/2986303105 Some rights reserved. This image is licensed with a Creative Commons Attribution, Non-Commercial, Share Alike license. http://creativecommons.org/licenses/by-nc-sa/2.0/deed.en http://creativecommons.org/licenses/by-nc-sa/2.0/deed.en

46. H1. Performance expectancy will not have a positive effect on behavioral intention to use mobile learning. H2. Effort expectancy will not have a positive effect on behavioral intention to use mobile learning. H3. Social influence will not have a positive effect on behavioral intention to use mobile learning. H4. Self-management of learning will not have a positive effect on behavioral intention to use mobile learning. H5. Perceived playfulness will not have a positive effect on behavioral intention to use mobile learning. H6. Voluntariness of use will not have a positive effect on behavioral intention to use mobile learning. H7. Behavioral intention will not have a positive influence on mobile learning intention to use. H8. Facilitating conditions will not have a positive influence on mobile learning intention to use. 46Copyright Robin Lee Donaldson. All rights reserved.